The final will cover:

counting (principles of counting, permutations, combinations, binomial coefficients, binomial theorem)
pigeonhole principle
basics of discrete probability theory
conditional probability
Bayes theorem
random variables, both continuous and discrete (including Bernoulli, Binomial, Geometric, Poisson, Uniform, Exponential and Normal)
expectation
variance
probability mass functions (pmf) /probability density functions (pdf) /cumulative distribution functions (CDF)
linearity of expectation
independence of random variables, joint distributions and marginal distributions
linearity of variance for independent random variables
E(XY) = E(X)E(Y) if X and Y are independent.
law of total probability and law of total expectation for discrete random variables.
randomized algorithms
continuous random variables
tail bounds (Markov, Chebychev, Chernoff)
Law of large numbers (just what it is) and Central Limit Theorem
maximum likelihood estimation
anything covered on the homeworks and all daily problems.

About final:

The final will be in Kane 120.
The final will be slightly more focused on the material that wasn't covered in the midterm.
You can bring one page of notes (double-sided). No electronics of any kind.
You can use any facts listed on the slides or in the books without proof.